Raising finance is a necessary evil for many entrepreneurs. It is sometimes a reoccurring one. It’s a lot of effort, and it diverts your attention away from the main goal at hand: building a successful business. Fundraising may be challenging and demanding. If you are raising financing for an AI firm, the task may be considerably more onerous.

In this article, how to get funding for an AI startup is discussed.

Why are AI Startups different?

As with any other company, you must demonstrate traction, an experienced, strong, and motivated staff, and a market with growth potential. As if that wasn’t difficult enough, there are some additional obstacles with AI.

Creating AI products is typically an iterative process. It is impossible to predict how well the AI will perform and how much it will cost to develop from the start. As a result, creating the business case is more complex.

Data might also make your business more difficult. Unlike in traditional IT, data is an essential component of the product. AI cannot exist without data, which is difficult and expensive to obtain. Many people underestimate the amount of work that goes into ensuring the right amount of the right quality of data.

The Venture Capital’s AI understanding

You cannot rely on venture capitalists (VCs) to understand AI as well as you do. When venture capitalists consider investing in a SaaS (Software as a Service) startup, they are on familiar territory. They understand all of the intricacies, threats, and dynamics. When people look at AI-companies, their knowledge spans from absolutely none to profound specialists. That is an issue. To begin with, you may believe that being the expert when the VC is not will offer you an advantage. Unfortunately, that is not the case. When chatting with another expert, the conversation improves and becomes more fruitful. There will be more idea confusion when the VCs have minimal expertise of the issue.

Second, you must talk to several levels of comprehension at the same time. It’s difficult to prepare a pitch deck when you have to speak with both the expert and the novice. The same is true for the pitches themselves. However, during the pitches, you should be able to get a sense of the level of knowledge. Attempt to obtain this early on. But be cautious. Questions like “Do you comprehend AI?” are pointless. People, regardless of their comprehension, usually respond yes to inquiries like that. As a result, ask open-ended inquiries.

As a result, the VC’s knowledge differs, and you must keep this in mind at all times.

Preparations to get funding

Positioning

No matter how unique you believe your company and product are, they most likely aren’t. If there is one thing that VCs excel at, it is finding firms that do what you do. Sometimes these are competitors you’ve never heard of but are very similar, and sometimes they’re not at all but appear to be to the VC. Nonetheless, positioning is always the solution.

You must be quite clear about how you intend to position yourself in the market. Make sure your product positioning appears to be a well-thought-out decision. Be clear about how your product selections distinguish your organization. Maybe it’s the manner you collect data, how or where you deploy the product, or that you prioritized speed above quality. Anything is possible. Make it obvious and upfront why these options are beneficial for your consumers and your competition.

Be resistant to change. The world is changing, and technology is changing at a faster rate than ever before. As a result, you should understand how you will be immune to this shift. Perhaps it is your high stickiness, your position in an ecosystem, or your customer connection that is your weapon against change. It makes no difference as long as you have sound arguments.

Data and Algorithm

To begin with, according to a survey conducted by the investment company MMC Ventures, many firms that claim to employ AI do not. Don’t attempt to get away with anything here. Due diligence will be performed by VCs, and backtracking is never enjoyable. AI is not required to raise finance. You must have a solid scalable business. You are not an AI firm if you employ Google’s regular off-the-shelf AI. Being a technology or automation product is not inherently worse than being an AI company. It may save you time and effort not to focus on AI if you are not deeply involved in it.

You can still sell yourself as an AI firm if you use off-the-shelf AI in a creative way. Just keep it in marketing rather than the pitch deck.

The algorithm

You don’t have a brilliant algorithm. I’m sorry, but you just do not. Google will outperform whatever you spend a whole year creating. That is exactly how it is. Your algorithm is most likely nothing exceptional.

So, what’s the purpose if Google can do it better?

It’s a difficult one, and you should be prepared for any possible investor to question, “What if Google or another large tech company pursues this market tomorrow?” Digging deep into the verticals might be a viable strategy here. Big tech is strong because it is large, but as a result, it cannot specialise in verticals or specialised markets. This may be your advantage. Consider their off-the-shelf AI. Their vision can detect a chair, but if you ask it what the local brand is, it probably won’t know. When developing your pitch, look for edges like those.

The Data

Data provides a genuine competitive edge. Make it a point to explain to investors how your data differs from that of your rivals. You may obtain data at a reduced cost; it may also be of greater quality or volume.

Many AI firms are taken aback by the cost of maintaining the data flow to the AI. Because it is the lifeblood of artificial intelligence, it cannot be turned off. Make sure you can demonstrate a high level of cash efficiency here. Simply keeping their AI alive might cause your competition to run out of money.

If you haven’t heard of it, active learning is a machine learning approach that can assist you in this situation.

Scaling

One challenge that arises is how to scale products when entering new markets. Do you need to make a lot of changes or collect a lot of new data in order for the product to function in different nations or verticals?

Yes, scalability is critical. You must grow your product in order to transform your firm from a small to a large corporation.